Machine learning: Physics and Data

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Related lectures (52)

Dynamics: Laws and Concepts Log in to Mediaspace to watch this video

Covers the fundamental laws of dynamics, including Newton's three laws of motion, forces, momentum, and center of mass.

Untitled Log in to Mediaspace to watch this video

Data Representations and Processing Log in to Mediaspace to watch this video

Discusses overfitting, model selection, cross-validation, regularization, data representations, and handling imbalanced data in machine learning.

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Execution Models for Distributed Computing - 2nd generation Log in to Mediaspace to watch this video

Explores the 2nd generation of execution models for distributed computing, focusing on Spark and Resilient Distributed Datasets (RDDs).

Conditional Density and Expectation Log in to Mediaspace to watch this video

Explores conditional density, expectations, and independence of random variables with practical examples.

Scattering matrix: definition and applications Log in to Mediaspace to watch this video

Explores the scattering matrix definition and its applications in microwave circuits.

Turbulence: Numerical Flow Simulation Log in to Mediaspace to watch this video

Explores turbulence characteristics, simulation methods, and modeling challenges, providing guidelines for choosing and validating turbulence models.

Privacy: Paradigms and Adversaries Log in to Mediaspace to watch this video

Covers privacy paradigms, data collection by companies, legal frameworks, trust in data providers, and the security vs. privacy debate.

Advanced Physics I: Rotational Dynamics Log in to Mediaspace to watch this video

Covers advanced topics in rotational dynamics, including gyroscopic effects and solid body dynamics, with practical exercises and announcements.

Semi-Structured Data Log in to Mediaspace to watch this video

Explores semi-structured data, embedding schema information to explain data values and relationships, discussing XML, schema-less data benefits, and serialization.

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